Row generator
The long_sequence() function may be used as a row generator to create table
data for testing. Basic usage of this function involves providing the number of
iterations required. Deterministic pseudo-random behavior can be achieved by
providing seed values when calling the function.
This function is commonly used in combination with random generator functions to produce mock data.
long_sequence
long_sequence(iterations)- generates rowslong_sequence(iterations, seed1, seed2)- generates rows deterministically
Arguments:
-iterations: is a long representing the number of rows to generate. -seed1
and seed2 are long64 representing both parts of a long128 seed.
Row generation
The long_sequence() function can be used to generate very large datasets for
testing e.g. billions of rows.
long_sequence(iterations) is used to:
- Generate a number of rows defined by
iterations. - Generate a column
x:longof monotonically increasing long integers starting from 1, which can be accessed for queries.
Random number seed
When long_sequence is used conjointly with
random generators, these
values are usually generated at random. The function supports a seed to be
passed in order to produce deterministic results.
Deterministic procedural generation makes it easy to test on vasts amounts of data without actually moving large files around across machines. Using the same seed on any machine at any time will consistently produce the same results for all random functions.
Examples:
SELECT x, rnd_double()
FROM long_sequence(5);
| x | rnd_double |
|---|---|
| 1 | 0.3279246687 |
| 2 | 0.8341038236 |
| 3 | 0.1023834675 |
| 4 | 0.9130602021 |
| 5 | 0.718276777 |
SELECT x, x*x
FROM long_sequence(5);
| x | x*x |
|---|---|
| 1 | 1 |
| 2 | 4 |
| 3 | 9 |
| 4 | 16 |
| 5 | 25 |
SELECT rnd_double()
FROM long_sequence(2,128349234,4327897);
The results below will be the same on any machine at any time as long as they use the same seed in long_sequence.
| rnd_double |
|---|
| 0.8251337821991485 |
| 0.2714941145110299 |
generate_series
Rather than generating a fixed number of entries, generate_series can instead be used
to generate entries within a bounded range.
This function supports LONG and DOUBLE generation. There is also a TIMESTAMP generating version,
which can be found here
The start and end values are interchangeable, and a negative step value can be used to
obtain the series in reverse order.
The series is inclusive on both ends.
Arguments:
generate_series(start_long, end_long, step_long) - generates a series of longs.
generate_series(start_double, end_double, step_double) - generates a series of doubles.
Return value:
Return value type is `times--- title: Row generator sidebar_label: Row generator description: Row generator function reference documentation.
The long_sequence() function may be used as a row generator to create table
data for testing. Basic usage of this function involves providing the number of
iterations required. Deterministic pseudo-random behavior can be achieved by
providing seed values when calling the function.
This function is commonly used in combination with random generator functions to produce mock data.
long_sequence
long_sequence(iterations)- generates rowslong_sequence(iterations, seed1, seed2)- generates rows deterministically
Arguments:
-iterations: is a long representing the number of rows to generate. -seed1
and seed2 are long64 representing both parts of a long128 seed.
Row generation
The long_sequence() function can be used to generate very large datasets for
testing e.g. billions of rows.
long_sequence(iterations) is used to:
- Generate a number of rows defined by
iterations. - Generate a column
x:longof monotonically increasing long integers starting from 1, which can be accessed for queries.
Random number seed
When long_sequence is used conjointly with
random generators, these
values are usually generated at random. The function supports a seed to be
passed in order to produce deterministic results.
Deterministic procedural generation makes it easy to test on vasts amounts of data without actually moving large files around across machines. Using the same seed on any machine at any time will consistently produce the same results for all random functions.
Examples:
SELECT x, rnd_double()
FROM long_sequence(5);
| x | rnd_double |
|---|---|
| 1 | 0.3279246687 |
| 2 | 0.8341038236 |
| 3 | 0.1023834675 |
| 4 | 0.9130602021 |
| 5 | 0.718276777 |
SELECT x, x*x
FROM long_sequence(5);
| x | x*x |
|---|---|
| 1 | 1 |
| 2 | 4 |
| 3 | 9 |
| 4 | 16 |
| 5 | 25 |
SELECT rnd_double()
FROM long_sequence(2,128349234,4327897);
The results below will be the same on any machine at any time as long as they use the same seed in long_sequence.
| rnd_double |
|---|
| 0.8251337821991485 |
| 0.2714941145110299 |
generate_series
Rather than generating a fixed number of entries, generate_series can instead be used
to generate entries within a bounded range.
This function supports LONG and DOUBLE generation. There is also a TIMESTAMP generating version,
which can be found here
The start and end values are interchangeable, and a negative step value can be used to
obtain the series in reverse order.
The series is inclusive on both ends.
The final argument is optional, and defaults to 1.
As a pseudo-table, the function can be called in isolation (generate_series()), or as
part of a select (SELECT * FROM generate_series()).
Arguments:
generate_series(start_long, end_long, step_long) - generates a series of longs.
generate_series(start_double, end_double, step_double) - generates a series of doubles.
Return value:
Return value type is long or double.
Examples:
generate_series(-3, 3, 1);
-- or
generate_series(-3, 3);
| generate_series |
|---|
| -3 |
| -2 |
| -1 |
| 0 |
| 1 |
| 2 |
| 3 |
generate_series(3, -3, -1);
| generate_series |
|---|
| 3 |
| 2 |
| 1 |
| 0 |
| -1 |
| -2 |
| -3 |
generate_series(-3d, 3d, 1d);
-- or
generate_series(-3d, 3d);
| generate_series |
|---|
| -3.0 |
| -2.0 |
| -1.0 |
| 0.0 |
| 1.0 |
| 2.0 |
| 3.0 |
generate_series(-3d, 3d, -1d);
| generate_series |
|---|
| 3.0 |
| 2.0 |
| 1.0 |
| 0.0 |
| -1.0 |
| -2.0 |
| -3.0 |